Faster decline and higher variability in the sea ice thickness of the marginal Arctic seas when accounting for dynamic snow cover

Abstract. Mean sea ice thickness is a sensitive indicator of Arctic climate change and is in long-term decline despite significant interannual variability. Current thickness estimations from satellite radar altimeters employ a snow climatology for converting range measurements to sea ice thickness, but this introduces unrealistically low interannual variability and trends. When the sea ice thickness in the period 2002–2018 is calculated using new snow data with more realistic variability and trends, we find mean sea ice thickness in four of the seven marginal seas to be declining between 60 %–100 % faster than when calculated with the conventional climatology. When analysed as an aggregate area, the mean sea ice thickness in the marginal seas is in statistically significant decline for 6 of 7 winter months. This is observed despite a 76 % increase in interannual variability between the methods in the same time period. On a seasonal timescale we find that snow data exert an increasingly strong control on thickness variability over the growth season, contributing 46 % in October but 70 % by April. Higher variability and faster decline in the sea ice thickness of the marginal seas has wide implications for our understanding of the polar climate system and our predictions for its change.

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Faster decline and higher variability in the sea ice thickness of the marginal Arctic seas

10.5194/tc-2020-282 ◽

2020 ◽

Author(s):

Robbie D. C. Mallett ◽

Julienne C. Stroeve ◽

Michel Tsamados ◽

Jack C. Landy ◽

Rosemary Willatt ◽

...

Keyword(s):

Sea Ice ◽

Interannual Variability ◽

Ice Thickness ◽

Arctic Seas ◽

Sea Ice Thickness ◽

Marginal Seas ◽

Thickness Variability ◽

Satellite Radar ◽

Arctic Climate Change ◽

Strong Control

Abstract. Mean sea ice thickness is a sensitive indicator of Arctic climate change and in long-term decline despite significant interannual variability. Current thickness estimations from satellite radar altimeters employ a snow climatology for converting range measurements to sea ice thickness, but this introduces unrealistically low interannual variability and trends. When the sea ice thickness in the period 2002–2018 is calculated using new snow data with more realistic variability and trends, we find mean sea ice thickness in three of the seven marginal seas to be declining between 70–100 % faster than when calculated with the conventional method. When analysed as an aggregate, the mean ice thickness in the marginal seas is now in statistically significant decline for four of seven winter months. This is observed despite a 58% increase in interannual variability between the methods in the same time period. On a seasonal timescale we find that snow data exerts an increasingly strong control on thickness variability over the growth season, contributing only 20 % in October but 72 % by April. Higher variability and faster decline in the sea ice thickness of the marginal seas has wide implications for our understanding of the polar climate system and our predictions for its change, as well as for stakeholders involved in Arctic shipping and natural resource extraction.

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Interannual sea ice thickness variability in the Bay of Bothnia

The Cryosphere ◽

10.5194/tc-12-3459-2018 ◽

2018 ◽

Vol 12 (11) ◽

pp. 3459-3476 ◽

Cited By ~ 5

Author(s):

Iina Ronkainen ◽

Jonni Lehtiranta ◽

Mikko Lensu ◽

Eero Rinne ◽

Jari Haapala ◽

...

Keyword(s):

Sea Ice ◽

Interannual Variability ◽

Thickness Distribution ◽

Ice Thickness ◽

Data Sets ◽

Sea Ice Extent ◽

Sea Ice Thickness ◽

Thickness Variability ◽

Fast Ice ◽

Ridged Ice

Abstract. While variations of Baltic Sea ice extent and thickness have been extensively studied, there is little information about drift ice thickness, distribution, and its variability. In our study, we quantify the interannual variability of sea ice thickness in the Bay of Bothnia during the years 2003–2016. We use various different data sets: official ice charts, drilling data from the regular monitoring stations in the coastal fast ice zone, and helicopter and shipborne electromagnetic soundings. We analyze the different data sets and compare them to each other to characterize the interannual variability, to discuss the ratio of level and deformed ice, and to derive ice thickness distributions in the drift ice zone. In the fast ice zone the average ice thickness is 0.58±0.13 m. Deformed ice increases the variability of ice conditions in the drift ice zone, where the average ice thickness is 0.92±0.33 m. On average, the fraction of deformed ice is 50 % to 70 % of the total volume. In heavily ridged ice regions near the coast, mean ice thickness is approximately half a meter thicker than that of pure thermodynamically grown fast ice. Drift ice exhibits larger interannual variability than fast ice.

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Interannual sea ice thickness variability in the Bay of Bothnia

10.5194/tc-2018-87 ◽

2018 ◽

Author(s):

Iina Ronkainen ◽

Jonni Lehtiranta ◽

Mikko Lensu ◽

Eero Rinne ◽

Jari Haapala ◽

...

Keyword(s):

Sea Ice ◽

Interannual Variability ◽

Thickness Distribution ◽

Ice Thickness ◽

Data Sets ◽

Sea Ice Extent ◽

Sea Ice Thickness ◽

Thickness Variability ◽

Fast Ice ◽

Ridged Ice

Abstract. While variations of Baltic Sea ice extent and fast ice thickness have been extensively studied, there is little information about the sea ice thickness distribution and its variability. In our study, we quantify the interannual variability of sea ice thickness in the Bay of Bothnia during the years 2003–2016. We use various different data sets: official ice charts, drilling data from the regular monitoring stations in the coastal fast ice zone and from helicopter- and ship-borne electromagnetic soundings. We analyze the different data sets and compare them to each other to characterize the interannual variability, to discuss the ratio of level and deformed ice, and to derive ice thickness distributions in the drift ice zone. In the fast ice zone the average ice thickness is 0.58 &pm; 0.13 m. Deformed ice increases the variability of ice conditions in the drift ice zone where the average ice thickness is 0.92 &pm; 0.33 m. In heavily ridged ice regions near the coast, mean ice thickness can be even manyfold thicker than in a pure thermodynamically grown fast ice. Drift ice exhibits larger inter-annual variability than fast ice.

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Characteristics of Sea-ice thickness and Snow-depth distributions of the Summer landfast ice in Lützow-Holm Bay, East Antarctica

Annals of Glaciology ◽

10.3189/172756406781811240 ◽

2006 ◽

Vol 44 ◽

pp. 281-287 ◽

Cited By ~ 9

Author(s):

Shotaro Uto ◽

Haruhito Shimoda ◽

Shuki Ushio

Keyword(s):

Sea Ice ◽

Interannual Variability ◽

Snow Depth ◽

East Antarctica ◽

Ice Thickness ◽

First Year ◽

Total Thickness ◽

Sea Ice Thickness ◽

Landfast Ice ◽

Northeasterly Wind

AbstractSea-ice observations have been conducted on board icebreaker shirase as a part of the Scientific programs of the Japanese Antarctic Research Expedition. We Summarize these to investigate Spatial and interannual variability of ice thickness and Snow depth of the Summer landfast ice in Lützow-Holm Bay, East Antarctica. Electromagnetic–inductive observations, which have been conducted Since 2000, provide total thickness distributions with high Spatial resolution. A clear discontinuity, which Separates thin first-year ice from thick multi-year ice, was observed in the total thickness distributions in two voyages. Comparison with Satellite images revealed that Such phenomena reflected the past breakup of the landfast ice. Within 20–30km from the Shore, total thickness as well as Snow depth decrease toward the Shore. This is due to the Snowdrift by the Strong northeasterly wind. Video observations of Sea-ice thickness and Snow depth were conducted on 11 voyages Since December 1987. Probability density functions derived from total thickness distributions in each year are categorized into three types: a thin-ice, thick-ice and intermediate type. Such interannual variability primarily depends on the extent and duration of the Successive break-up events.

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Winter Arctic sea ice freeboard, snow depth and thickness variability from ICESat-2 and NESOSIM

10.5194/egusphere-egu21-13779 ◽

2021 ◽

Author(s):

Alek Petty ◽

Nicole Keeney ◽

Alex Cabaj ◽

Paul Kushner ◽

Nathan Kurtz ◽

...

Keyword(s):

Sea Ice ◽

Snow Depth ◽

Arctic Sea Ice ◽

The Arctic ◽

Ice Thickness ◽

Sea Ice Thickness ◽

Ice Cloud ◽

Ice Drift ◽

Thickness Variability ◽

Arctic Ice

<div> <div> <div> <div> <p>National Aeronautics and Space Administration's (NASA's) Ice, Cloud, and land Elevation Satellite&#8208; 2 (ICESat&#8208;2) mission was launched in September 2018 and is now providing routine, very high&#8208;resolution estimates of surface height/type (the ATL07 product) and freeboard (the ATL10 product) across the Arctic and Southern Oceans. In recent work we used snow depth and density estimates from the NASA Eulerian Snow on Sea Ice Model (NESOSIM) together with ATL10 freeboard data to estimate sea ice thickness across the entire Arctic Ocean. Here we provide an overview of updates made to both the underlying ATL10 freeboard product and the NESOSIM model, and the subsequent impacts on our estimates of sea ice thickness including updated comparisons to the original ICESat mission and ESA&#8217;s CryoSat-2. Finally we compare our Arctic ice thickness estimates from the 2018-2019 and 2019-2020 winters and discuss possible causes of these differences based on an analysis of atmospheric data (ERA5), ice drift (NSIDC) and ice type (OSI SAF).</p> </div> </div> </div> </div>

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The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise

The Cryosphere ◽

10.5194/tc-9-37-2015 ◽

2015 ◽

Vol 9 (1) ◽

pp. 37-52 ◽

Cited By ~ 38

Author(s):

S. Kern ◽

K. Khvorostovsky ◽

H. Skourup ◽

E. Rinne ◽

Z. S. Parsakhoo ◽

...

Keyword(s):

Sea Ice ◽

Snow Depth ◽

Ice Thickness ◽

Data Sets ◽

Snow Density ◽

Radar Altimetry ◽

Sea Ice Thickness ◽

The Mean ◽

Satellite Radar ◽

Satellite Radar Altimetry

Abstract. We assess different methods and input parameters, namely snow depth, snow density and ice density, used in freeboard-to-thickness conversion of Arctic sea ice. This conversion is an important part of sea ice thickness retrieval from spaceborne altimetry. A data base is created comprising sea ice freeboard derived from satellite radar altimetry between 1993 and 2012 and co-locate observations of total (sea ice + snow) and sea ice freeboard from the Operation Ice Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) airborne campaigns, of sea ice draft from moored and submarine upward looking sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer (AMSR-E) and the Warren climatology (Warren et al., 1999). We compare the different data sets in spatiotemporal scales where satellite radar altimetry yields meaningful results. An inter-comparison of the snow depth data sets emphasizes the limited usefulness of Warren climatology snow depth for freeboard-to-thickness conversion under current Arctic Ocean conditions reported in other studies. We test different freeboard-to-thickness and freeboard-to-draft conversion approaches. The mean observed ULS sea ice draft agrees with the mean sea ice draft derived from radar altimetry within the uncertainty bounds of the data sets involved. However, none of the approaches are able to reproduce the seasonal cycle in sea ice draft observed by moored ULS. A sensitivity analysis of the freeboard-to-thickness conversion suggests that sea ice density is as important as snow depth.

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High interannual variability of sea ice thickness in the Arctic region

Nature ◽

10.1038/nature02050 ◽

2003 ◽

Vol 425 (6961) ◽

pp. 947-950 ◽

Cited By ~ 356

Author(s):

Seymour Laxon ◽

Neil Peacock ◽

Doug Smith

Keyword(s):

Sea Ice ◽

Interannual Variability ◽

Arctic Region ◽

The Arctic ◽

Ice Thickness ◽

Sea Ice Thickness ◽

The Arctic Region

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Assessment of contemporary satellite sea ice thickness products for Arctic sea ice

The Cryosphere ◽

10.5194/tc-13-1187-2019 ◽

2019 ◽

Vol 13 (4) ◽

pp. 1187-1213 ◽

Cited By ~ 9

Author(s):

Heidi Sallila ◽

Sinéad Louise Farrell ◽

Joshua McCurry ◽

Eero Rinne

Keyword(s):

Sea Ice ◽

Region Of Interest ◽

Arctic Sea Ice ◽

Ice Thickness ◽

Change Analysis ◽

Sea Ice Thickness ◽

Ship Traffic ◽

Marginal Seas ◽

Data Products ◽

Operational Activities

Abstract. Advances in remote sensing of sea ice over the past two decades have resulted in a wide variety of satellite-derived sea ice thickness data products becoming publicly available. Selecting the most appropriate product is challenging given end user objectives range from incorporating satellite-derived thickness information in operational activities, including sea ice forecasting, routing of maritime traffic and search and rescue, to climate change analysis, longer-term modelling, prediction and future planning. Depending on the use case, selecting the most suitable satellite data product can depend on the region of interest, data latency, and whether the data are provided routinely, for example via a climate or maritime service provider. Here we examine a suite of current sea ice thickness data products, collating key details of primary interest to end users. We assess 8 years of sea ice thickness observations derived from sensors on board the CryoSat-2 (CS2), Advanced Very-High-Resolution Radiometer (AVHRR) and Soil Moisture and Ocean Salinity (SMOS) satellites. We evaluate the satellite-only observations with independent ice draft and thickness measurements obtained from the Beaufort Gyre Exploration Project (BGEP) upward looking sonar (ULS) instruments and Operation IceBridge (OIB), respectively. We find a number of key differences among data products but find that products utilizing CS2-only measurements are reliable for sea ice thickness, particularly between ∼0.5 and 4 m. Among data compared, a blended CS2-SMOS product was the most reliable for thin ice. Ice thickness distributions at the end of winter appeared realistic when compared with independent ice draft measurements, with the exception of those derived from AVHRR. There is disagreement among the products in terms of the magnitude of the mean thickness trends, especially in spring 2017. Regional comparisons reveal noticeable differences in ice thickness between products, particularly in the marginal seas in areas of considerable ship traffic.

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Sea-ice thickness variability in Storfjorden, Svalbard

Annals of Glaciology ◽

10.3189/172756411795931561 ◽

2011 ◽

Vol 52 (57) ◽

pp. 61-68 ◽

Cited By ~ 16

Author(s):

S. Hendricks ◽

S. Gerland ◽

L.H. Smedsrud ◽

C. Haas ◽

A.A. Pfaffhuber ◽

...

Keyword(s):

Sea Ice ◽

Barents Sea ◽

Meteorological Data ◽

Ice Thickness ◽

Central Arctic Ocean ◽

Reanalysis Dataset ◽

Sea Ice Thickness ◽

Thickness Variability ◽

Fast Ice ◽

Thickness Variations

AbstractResults from electromagnetic induction surveys of sea-ice thickness in Storfjorden, Svalbard, reveal large interannual ice-thickness variations in a region which is typically characterized by a reoccurring polynya. the surveys were performed in March 2003, May 2006 and March 2007 with helicopter- and ship-based sensors. the thickness distributions are influenced by sea-ice and atmospheric boundary conditions 2 months prior to the surveys, which are assessed with synthetic aperture radar (SAR) images, regional QuikSCAT backscatter maps and wind information from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset. Locally formed thin ice from the Storfjorden polynya was frequently observed in 2003 and 2007 (mean thickness 0.55 and 0.37 m, respectively) because these years were characterized by prevailing northeasterly winds. In contrast, the entire fjord was covered with thick external sea ice in 2006 (mean thickness 2.21 m), when ice from the Barents Sea was driven into the fjord by predominantly southerly winds. the modal thickness of this external ice in 2006 increased from 1.2m in the northern fjord to 2.4 m in the southern fjord, indicating stronger deformation in the southern part. This dynamically thickened ice was even thicker than multi-year ice advected from the central Arctic Ocean in 2003 (mean thickness 1.83 m). the thermodynamic ice thickness of fast ice as boundary condition is investigated with a one-dimensional sea-ice growth model (1DICE) forced with meteorological data from the weather station at the island of Hopen, southeast of Storfjorden. the model results are in good agreement with the modal thicknesses of fast-ice measurements in all years.

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